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Adaptive Intelligence Standard (AIS-01) — Draft Structure

Draft standard framework for the Adaptive Intelligence Circle (AIC) — goal: to describe, standardize, and validate how to build "Adaptive Intelligence" systems that are open, adaptable, introspective, and secure.

Table of Contents

  1. Overview & Objectives
  2. Scope
  3. Terms & Definitions
  4. Foundational Principles
  5. Architecture Overview
  6. Adaptive Loop Description
  7. Module & Plugin Standards
  8. APIs & Data Formats
  9. DSL / Lua Bridge Specification
  10. Sandbox, Safety & Self‑Defense Rules
  11. Logging, Observability & Rollback
  12. Security, Privacy & Responsibility
  13. Test Suite & Compliance Criteria
  14. Governance, Contribution & Licensing
  15. Reference Implementation
  16. Use Cases
  17. Roadmap & Versioning
  18. References & Appendices

1. Overview & Objectives

  • The goal of AIS‑01: to define a set of principles, formats and Minimum API for Adaptive Intelligence systems to be:

  • interoperable;

  • verifiable adaptive behavior;

  • open and integrated into the OSS ecosystem.

  • Expected results: spec v0.1 (living document) + reference implementation + compliance tests.

2. Scope of application

  • System type: agent, runtime, middleware, introspective compilers, adaptive OS modules.
  • Level of application: core primitives (adaptive loop, state model, policy engine), plugin contract, observability contract.
  • What is NOT in scope: detailed description of the internal ML/LLM model (only interface/hook description).

3. Terms & Definitions

  • Adaptive Agent, Adaptive Loop, Introspection, Trust Memory, Rollback Policy, Sandbox Context, Behavior Engine, Plugin Contract, Compliance Suite, etc.
  • Quantitative descriptions for vague terms (e.g., "level of adaptivity" 0..3).

4. Foundational Principles

  • Open & Transparent
  • Composability (module‑first)
  • Reproducibility & Core Determinism
  • Least Privilege & Sandboxing
  • Human‑in‑the‑loop by Default
  • Traceability & Auditability

5. Overall Architecture

  • Layer Diagram: Application → Behavior Engine → Adaptive Core (Loop Controller, State Model, Experience Store) → Runtime/Plugin Host → Sandbox/OS

  • Main Components:

  • Adaptive Core (controller, scheduler)

  • State Model & Trust Memory

  • Policy Engine / Behavior Rules

  • Plugin Host / Loader (Lua/C++ bridge)

  • Observability & Telemetry

  • Compliance Monitor & Rollback Manager

6. Adaptive Loop Description

  • Phases: Sense → Interpret → Decide → Act → Learn → (optionally) Rollback
  • Data exchange between phases (template schema)
  • Time and constraints (hard/soft deadlines)
  • Hooks for introspection and human override

7. Module & plugin standards

  • File layout & naming convention
  • Module metadata (manifest): id, version, capabilities, dependencies, permissions
  • Lifecycle methods: init, probe, run, quiesce, shutdown
  • Semantic versioning & compatibility rules

8. Interface (API) and data format

  • Spec REST/gRPC/local IPC contracts for:

  • State read/write

  • Event publish/subscribe

  • Policy evaluation query

  • Telemetry ingestion

  • JSON schemas / protobuf examples for core messages

9. DSL / Lua bridge specification

  • Goal: how plugin authors write rules/behaviors in Lua and securely link to core C++
  • API exposed to Lua (sandboxed): read_state(key), propose_action(action), request_rollback(reason)
  • Security model: capability tokens, call timeouts, memory quotas
  • Serialization rules between Lua and host

10. Sandbox, Safety & Self‑defense rules

  • Sandbox primitives: resource limits, syscall filtering, network egress policy
  • Safety policies: forbidden actions, escalation rules, kill switches
  • Self‑defense model: anomaly detector → containment → notification → forensic log
  • Human emergency override & policy approval workflow

11. Logging, Observability & Rollback

  • Standard log format (structured logs), correlation IDs, causal traces
  • Telemetry metrics (latency, adaptivity score, policy violations)
  • Rollback policy definition: scopes, retention, automated vs manual
  • Forensics and reproducibility: snapshotting, deterministic replay

12. Bao Confidentiality, Privacy and Responsibility

  • Data classification & handling rules
  • Access control model (RBAC / capability‑based)
  • Compliance with privacy principles (anonymization, minimal retention)
  • Responsible disclosure & vulnerability handling

13. Test suite & Compliance criteria

  • Test categories: unit (determinism), integration (adaptive loop behavior), security (sandbox escape), performance (throughput), reproducibility (replay tests)
  • Compliance levels: AIS‑C0 (baseline), AIS‑C1 (recommended), AIS‑C2 (strict)
  • Reference test runner, how to publish results (badging)

14. Governance, Contribution & Licensing

  • Suggested licenses for core/spec (Apache‑2.0 + contributor license optional agreements)
  • Governance model options: benevolent dictator, meritocratic council, foundation model
  • Contribution flow: issue → RFC → implementation → compliance test → approval

15. Reference Implementation

  • Minimal core repo structure
  • Example modules: state_store, behavior_rule_engine, lua_plugin_host, rollback_manager
  • Quickstart guide: build → run → run sample scenario

16. Use cases

  • Intrusion detection + adaptive rollback
  • Personalization proxy for vehicle driver (AIForDriver example)
  • Cooperative multi‑agent adaptation (research scenario)
  • Controlled model fine‑tuning via policy engine

17. Application & Versioning Roadmap

  • AIS‑01 milestones: spec v0.1 draft → ref impl v0.1 → compliance suite v0.1 → community review
  • Versioning rules: semantic + capability tags

18. References & Appendices

  • Template manifest, JSON schema, protobufs
  • Template CONTRIBUTING.md, CODE_OF_CONDUCT.md, GOVERNANCE.md
  • Glossary and academic references